Image quantization parameter encoding method and image quantization parameter decoding method

ABSTRACT

Disclosed are image quantization parameter decoding method and systems for decoding a quantization parameter for a video decoding process that is based on context-based adaptive binary arithmetic coding. In one embodiment, an image quantization parameter decoding method includes binary-arithmetic-decoding a first bin indicating whether or not a delta quantization parameter is significant, other bins, which are subsequent to the first bin, indicating an absolute value of the delta quantization parameter, and a sign bin, which is subsequent to the other bins, indicating whether the delta quantization parameter is positive or negative. The method further includes generating a delta quantization parameter by de-binarizing the first bin, the other bins and the sign bin. The method further includes generating a re-constructed quantization parameter by adding a predicted quantization parameter to the delta quantization parameter. The binary-arithmetic-decoding is performed using contexts for the first bin and the other bins, and using no context for the sign bin.

TECHNICAL FIELD

The present invention relates to a technique of encoding an imagequantization parameter for image encoding that uses context-basedadaptive binary arithmetic coding, and for example relates to an imagequantization parameter encoding method, an image quantization parameterdecoding method, an image quantization parameter encoder, an imagequantization parameter decoder, an image quantization parameter encodingprogram, and an image quantization parameter decoding program that aresuitably applicable to an image encoding device, an image decodingdevice, and the like.

BACKGROUND ART

Non Patent Literatures (NPLs) 1 and 2 each disclose an image encodingtechnique that uses context-based adaptive binary arithmetic coding(CABAC).

FIG. 14 is a block diagram showing a structure of an image quantizationparameter encoding device in the image encoding technique that usesCABAC. The image quantization parameter encoder shown in FIG. 14(hereafter referred to as the typical image quantization parameterencoder) includes a predictor 101, a buffer 102, a binarizer 1030, anadaptive binary arithmetic encoder 104, and a switch (SW) 111.

A predicted quantization parameter (predicted QP: PQP) supplied from thepredictor 101 is subtracted from a quantization parameter (QP) input tothe typical image quantization parameter encoder. The QP from which thePQP has been subtracted is referred to as a delta quantization parameter(delta QP: DQP).

In NPL 1, the PQP is a reconstructed quantization parameter (lastreconstructed QP: LastRQP) of a last reconstructed image block. In NPL2, the PQP is a reconstructed quantization parameter (left reconstructedQP; LeftRQP) of a left adjacent image block or a reconstructedquantization parameter (LastRQP) of a last reconstructed image block.

The PQP is added to the DQP and the sum is stored in the buffer 102 as areconstructed quantization parameter (reconstructed QP: RQP), forsubsequent quantization parameter encoding.

The binarizer 1030 binarizes the DQP to obtain a bin string. One bit ofthe bin string is referred to as a bin. In the bin string, a bin that isbinary arithmetic encoded first is referred to as the first bin (1^(st)bin), a bin that is binary arithmetic encoded second is referred to asthe second bin (2^(nd) bin), and a bin that is binary arithmetic encodednth is referred to as the nth bin (n^(th) bin). The bin and the binstring are defined in 3.9 and 3.12 in NPL 1.

FIG. 15 is an explanatory diagram showing a correspondence table betweenthe DQP (rightmost column) and the bin string (center column) in NPLs 1and 2.

A bin string index in the leftmost column in FIG. 15 indicates an indexof a bin string corresponding to a DQP value. The bin string index is 1in the case where the DQP is 0, 2*DQP−1 in the case where the DQP isgreater than 0, and −2*DQP+1 in the case where the DQP is less than 0(where “* ” denotes multiplication).

A context index in the lowermost row in FIG. 15 indicates an index of acontext used for binary arithmetic encoding of a bin in a correspondingcolumn. For example, the bin string corresponding to DQP=−1 is 110 inwhich the value of the first bin is 1, the value of the second bin is 1,and the value of the third bin is 0. The context index used for binaryarithmetic encoding of the first bin is 0; the context index used forbinary arithmetic encoding of the second bin is 2, and the context indexused for binary arithmetic encoding of the third bin is 3. The contextmentioned here is a combination of a most probable symbol (PS) of thebin and its probability,

The adaptive binary arithmetic encoder 104 binary arithmetic encodeseach bin of the bin string supplied via the switch 111 beginning withthe first bin, using the context associated with the correspondingcontext index. The adaptive binary arithmetic encoder 104 also updatesthe context associated with the context index according to the value ofthe binary arithmetic encoded bin, for subsequent binary arithmeticencoding. Detailed operations of adaptive binary arithmetic encoding aredescribed in 9.3.4 in NPL 1.

The typical quantization parameter encoder encodes the input imagequantization parameter based on the above-mentioned operations.

CITATION LIST Non Patent Literature(s)

NPL 1: ISO/IEC 14496-10 Advanced Video Coding

NPL 2: “WD3: Working Draft 3 of High-Efficiency Video Coding”, Document:JCTVC-E603, Joint Collaborative Team on video Coding (JCT-VC) of ITU-TSG16 WP3 and ISO/IEC JTC1/SC29/WG11 5th Meeting: Geneva, CH, 16-23 Mar.,2011

SUMMARY OF INVENTION Technical Problem

As can be seen from FIG. 15, the typical quantization parameter encoderperforms binarization without distinguishing between information aboutwhether the significant DQP is positive or negative and informationabout the absolute value of the significant DQP. The typicalquantization parameter encoder therefore has a problem of being unableto suitably encode the significant DQP due to the following threefactors.

The first factor is that, since the second bin (bin in the column“2^(nd)”) and the subsequent bins (bins in the columns from “3^(rd)”onward) include information about three or more states which cannot beexpressed by one bin, it is impossible to binary arithmetic encode thebins using appropriate contexts. Information that can be expressed byone bin is information of which one of two states holds true. However,the second bin and the subsequent bins include information about threeor more states which cannot be expressed by one bin. In detail, in FIG.15, the second bin includes information of whether the DQP is positiveor negative and information indicating whether or not the absolute valueof the significant DQP is greater than or equal to 1. The subsequentbins from the third bin (in the columns from “3^(rd)” onward) includeinformation of whether the DQP is positive or negative and informationindicating the magnitude of the absolute value of the significant DQP.Hence, it is impossible to binary arithmetic encode, with appropriatecontexts, the second bin and the subsequent bins including informationabout three or more states which cannot be expressed by one bin.

The second factor is that redundant bins cannot be efficiently reducedeven in the case where the DQP range is known. For example, the DQPrange defined in NPLs 1 and 2 is from −26 to 25, which is asymmetricbetween positive and negative. In FIG. 15, DQP=−26 needs to be encodedwithout reducing the redundant 52nd and 53rd bins, due to the presenceof the bin string of DQP=26 that is not transmitted.

The third factor is that the number of bins included in the bin stringhandled by the typical quantization parameter encoder is approximatelytwice the number of bins in the case of separately binarizing theinformation of whether the significant DQP is positive or negative andthe absolute value of the significant DQP, A large number of bins leadsto an increase in the amount of encoded data and a decrease in the speedof the DQP encoding process and decoding process.

The present invention has an object of enabling suitable encoding of animage quantization parameter for image encoding that uses context-basedadaptive binary arithmetic coding, by resolving each of theabove-mentioned factors,

Solution to Problem

An image quantization parameter encoding method according to the presentinvention is an image quantization parameter encoding method forencoding a quantization parameter for a video encoding process that isbased on context-based adaptive binary arithmetic coding, the imagequantization parameter encoding method including: generating a predictedquantization parameter from a past reconstructed quantization parameter;generating a delta quantization parameter from a quantization parameterand the predicted quantization parameter; binary arithmetic encoding afirst bin indicating whether or not the delta quantization parameter issignificant, other bins indicating an absolute value of the deltaquantization parameter, and a bin indicating whether the deltaquantization parameter is positive or negative, in the case where thedelta quantization parameter is significant; and reducing one or more ofthe other bins using a range of the delta quantization parameter.

An image quantization parameter decoding method according to the presentinvention is an image quantization parameter decoding method fordecoding a quantization parameter for a video decoding process that isbased on context-based adaptive binary arithmetic coding, the imagequantization parameter decoding method including: generating a predictedquantization parameter from a past reconstructed quantization parameter;binary arithmetic decoding a first bin indicating whether or not a deltaquantization parameter is significant, other bins indicating an absolutevalue of the delta quantization parameter, and a bin indicating whetherthe delta quantization parameter is positive or negative; and estimatingone or more of the other bins reduced in a video encoding process, usinga range of the delta quantization parameter.

An image quantization parameter encoder according to the presentinvention is an image quantization parameter encoder for encoding aquantization parameter for a video encoding process that is based oncontext-based adaptive binary arithmetic coding, the image quantizationparameter encoder including: prediction means for generating a predictedquantization parameter from a past reconstructed quantization parameter;computing means for generating a delta quantization parameter from aquantization parameter and the predicted quantization parameter;quantization parameter encoding means for binary arithmetic encoding afirst bin indicating whether or not the delta quantization parameter issignificant, other bins indicating an absolute value of the deltaquantization parameter, and a bin indicating whether the deltaquantization parameter is positive or negative, in the case where thedelta quantization parameter is significant; and redundancy suppressionmeans for reducing one or more of the other bins using a range of thedelta quantization parameter,

An image quantization parameter decoder according to the presentinvention is an image quantization parameter decoder for decoding aquantization parameter for a video decoding process that is based oncontext-based adaptive binary arithmetic coding, the image quantizationparameter decoder including: prediction means for generating a predictedquantization parameter from a past reconstructed quantization parameter;quantization parameter decoding means for binary arithmetic decoding afirst bin indicating whether or not a delta quantization parameter issignificant, other bins indicating an absolute value of the deltaquantization parameter, and a bin indicating whether the deltaquantization parameter is positive or negative; and estimation means forestimating one or more of the other bins reduced in a video encodingprocess, using a range of the delta quantization parameter.

An image quantization parameter encoding program according to thepresent invention causes a computer in an image quantization parameterencoder for encoding a quantization parameter for a video encodingprocess that is based on context-based adaptive binary arithmeticcoding, to execute: a process of generating a predicted quantizationparameter from a past reconstructed quantization parameter; a process ofgenerating a delta quantization parameter from a quantization parameterand the predicted quantization parameter; a process of binary arithmeticencoding a first bin indicating whether or not the delta quantizationparameter is significant, other bins indicating an absolute value of thedelta quantization parameter, and a bin indicating whether the deltaquantization parameter is positive or negative, in the case where thedelta quantization parameter is significant; and a process of reducingone or more of the other bins using a range of the delta quantizationparameter.

An image quantization parameter decoding program according to thepresent invention causes a computer in an image quantization parameterdecoder for decoding a quantization parameter for a video decodingprocess that is based on context-based adaptive binary arithmeticcoding, to execute: a process of generating a predicted quantizationparameter from a past reconstructed quantization parameter; a process ofbinary arithmetic decoding a first bin indicating whether or not a delta

quantization parameter is significant, other bins indicating an absolutevalue of the delta quantization parameter, and a bin indicating whetherthe delta quantization parameter is positive or negative; and a processof estimating one or more of the other bins reduced in a video encodingprocess, using a range of the delta quantization parameter.

Advantageous Effect of Invention

According to the present invention, it is possible to suitably encode animage quantization parameter for image encoding that uses context-basedadaptive binary arithmetic coding.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a block diagram showing a structure of an image quantizationparameter encoder in Exemplary Embodiment 1.

FIG. 2 is a flowchart showing operations of the image quantizationparameter encoder in Exemplary Embodiment 1.

FIG. 3 is an explanatory diagram showing an example of a correspondencetable between a DQP and a bin string.

FIG. 4 is an explanatory diagram showing a pseudo program for convertingthe DQP to the bin string.

FIG. 5 is a block diagram showing a structure of an image quantizationparameter decoder in Exemplary Embodiment 2.

FIG. 6 is a flowchart showing operations of the image quantizationparameter decoder in Exemplary Embodiment 2.

FIG. 7 is a block diagram showing a structure of an image quantizationparameter encoder in Exemplary Embodiment 3.

FIG. 8 is a block diagram showing a structure of an image quantizationparameter decoder in Exemplary Embodiment 3.

FIG. 9 is an explanatory diagram showing a pseudo program for convertingthe DQP to the bin string.

FIG. 10 is an explanatory diagram showing another example of thecorrespondence table between the DQP and the bin string.

FIG. 11 is a block diagram showing an example of a structure of aninformation processing system capable of realizing functions of an imagequantization parameter encoder and an image quantization parameterdecoder according to the present invention.

FIG. 12 is a block diagram showing characteristic components in an imagequantization parameter encoder according to the present invention.

FIG. 13 is a block diagram showing characteristic components in an imagequantization parameter decoder according to the present invention.

FIG. 14 is a block diagram showing a structure of a typical imagequantization parameter encoder.

FIG. 15 is an explanatory diagram showing a typical example of acorrespondence table between a DQP and a bin string.

DESCRIPTION OF EMBODIMENTS

The following describes exemplary embodiments of the present inventionwith reference to drawings.

Exemplary Embodiment 1

FIG. 1 is a block diagram showing a structure of an image quantizationparameter encoder in Exemplary Embodiment 1 of the present invention.The image quantization parameter encoder shown in FIG. 1 includes apredictor 101, a buffer 102, a binarizer 1031, an adaptive binaryarithmetic encoder 104, a binary arithmetic encoder 105, a switch (SW)111, and a switch (SW) 112/

A predicted quantization parameter PQP supplied from the predictor 101is subtracted from a quantization parameter QP input to the imagequantization parameter encoder.

The PQP is added to a delta quantization parameter DQP (DQP=QP−PQP) andthe sum is stored in the buffer 102 as a reconstructed quantizationparameter RQP (RQP=DQP+PQP), for subsequent quantization parameterencoding.

The binarizer 1031 which is a feature of the present invention binarizesthe DQP using a combination of a minimum DQP (minDQP<0) and a maximumDQP (maxDQP>0). In detail, the binarizer 1031 first computes the firstbin of the DQP and a maximum number cMax (i.e. a value obtained bysubtracting 1, which corresponds to the first bin, from a larger one ofthe absolute values of minDQP and maxDQP) of the subsequent bins thatrelate to the absolute value of the DQP, by the following equations.

bin(1)=func1(DQP)   (1)

cMax=max(|minDQP|,|maxDQP|)1   (2).

When cMax≧1, the binarizer 1031 computes bin(n) (n=2, . . .,min(1+|DQP|, 1+cMax)) by the following equation.

bin(n)=func2(n−2,cMax,|DQP|−1)   (3).

Here, func2 (a, b, c) is a function that returns 1 if b and c are equal,returns 1 if c is less than b and a is less than c, and returns 0otherwise (if c is less than b and a and c are equal). The bins (withsyntax element value |DQP|) of the bin string that relate to theabsolute value of the DQP and are obtained by equation (3) are the sameas the bins of the bin string obtained by the truncated unary (TU)binarization process described in 9.3.2.2 in NPL 1.

As is clear from equation (3), the bins of the bin string that relate tothe absolute value of the DQP and are obtained by equation (3) are thebins of the bin string made non-redundant based on the DQP range(maximum value of the absolute values of the minimum DQP and the maximumDQP).

The binarizer 1031 binarizes information indicating whether thesignificant DQP is positive or negative by associating it with a signbin (Signbin), by the following equation.

Signbin=func3(DQP)   (4).

Here, func3(a, b) is a function that returns 1 if a is less than b andreturns 0 otherwise, and func3(a) is a function that returns 0 if a ispositive and returns 1 if a is not positive. As is clear from equations(2), (3), and (4), bin(n) (n=2, 3, . . . ) is encoded only in the casewhere the DQP has a significant value (note that the Signbin is the lastbin).

The adaptive binary arithmetic encoder 104 binary arithmetic encodeseach bin (bin(n):n=1, 2, . . . , min(1+|DQP|,1+cMax)), other than theSignbin, of the bin string supplied via the switch 111 using the contextassociated with the context index corresponding to the bin, and outputsthe encoded data via the switch 112. The adaptive binary arithmeticencoder 104 also updates the context associated with the context indexaccording to the value of the binary arithmetic encoded bin, forsubsequent binary arithmetic encoding.

The binary arithmetic encoder 105 binary arithmetic encodes, with equalprobability, the Signbin of the bin string supplied via the switch 111,and outputs the encoded data via the switch 112.

This completes the description of the structure of the imagequantization parameter encoder in this exemplary embodiment.

The following describes operations of the binarizer 1031, the adaptivebinary arithmetic encoder 104, and the binary arithmetic encoder 105which are features of the image quantization parameter encoder in thisexemplary embodiment, using a flowchart in FIG. 2.

The process starts, with the adaptive binary arithmetic encoder 104setting an initial value parameter n to 2.

In step S101, the binarizer 1031 binarizes the DQP in a manner that theinformation indicating whether or not the DQP is significant isassociated with the first bin, the information indicating the absolutevalue of the DQP is associated with the second and subsequent bins, andthe information indicating whether or not the significant DQP ispositive is associated with the Signbin.

In step S102, the adaptive binary arithmetic encoder 104 adaptive binaryarithmetic encodes bin(1).

In step S103, the binary arithmetic encoder 105 determines whether ornot the DQP is significant. In the case where the DQP is significant,the process proceeds to step S104. Otherwise, the process ends.

In step S104, the adaptive binary arithmetic encoder 104 adaptive binaryarithmetic encodes bin(n).

In step S105, the adaptive binary arithmetic encoder 104 determineswhether or not all bins of the bin string have been encoded. In the casewhere all bins have been encoded, the process proceeds to step S106.Otherwise, the adaptive binary arithmetic encoder 104 increments n andthe process proceeds to step S104, to adaptive binary arithmetic encodethe subsequent bin(n).

In step S106, the binary arithmetic encoder 105 binary arithmeticencodes the Signbin. The process then ends.

This completes the description of the operations of the binarizer 1031,the adaptive binary arithmetic encoder 104, and the binary arithmeticencoder 105 which are features of the image quantization parameterencoder in this exemplary embodiment.

FIG. 3 is an explanatory diagram showing an example of a correspondencetable between |DQP| (leftmost column) and the bin string (center column)according to the present invention.

In FIG. 3, X in the Signbin column of the bin string represents 1-bitinformation indicating whether or not the DQP is positive, i.e. whetherthe DQP is positive or negative. Suppose X=0 denotes positive and X=1denotes negative. Then, for example, the bin string of DQP=1 is 100, andthe bin string of DQP=−1 is 101. Moreover, na in the context index rowdenotes that no context is used (i.e. the most probable symbol and itsprobability are fixed).

FIG. 4 is an explanatory diagram showing a pseudo program for generatinga bin string corresponding to a DQP of a value synVal, whereminDQP=−(26+QpBdOffset_(Y)/2) and maxDQP=(25+QpBdOffset_(Y)/2).According to equation (2), cMax=max(|26+QpBdOffset_(Y)/2|,|25+QpBdOffset_(Y)/2|)−1 =26+QpBdOffset_(Y)/2−1=25+QpBdOffset_(Y)/2.Note that the definitions of the arithmetic operations used in thepseudo program are in accordance with the definitions in “5 Conventions”in NPL 2.

The binarization process according to the present invention resolves thethree factors causing the problem mentioned above, as follows.

The first factor is resolved by binary arithmetic encoding the secondbin and the subsequent bins using appropriate contexts. In FIG. 3, thesecond bin indicates only the information of whether or not the absolutevalue of the DQP is greater than 1, that is, information of which one oftwo states holds true. The third and subsequent bins indicate only theinformation of whether or not the absolute value of the DQP is greaterthan a given value, that is, information of which one of two statesholds true, as with the second bin. The Signbin indicates only theinformation of whether the DQP is positive or negative, that is,information of which one of two states holds true. Therefore, the secondbin and the Signbin are binary arithmetic encoded using appropriatecontexts.

The second factor is resolved because the encoder can efficiently reduceredundant bins using the DQP range. In detail, in FIG. 3, in the case ofencoding DQP=−26, the redundant 27th bin does not need to be encodedbecause the decoder is able to identify DQP=−26 when the 26th bin is 1on the ground that the minimum value of the DQP is −26.

The third factor is resolved because the number of bins included in thebin string in this exemplary embodiment is the same as the number ofbins in the case of separately binarizing the information of whether thesignificant DQP is positive or negative and the absolute value of thesignificant DQP, as is clear from the comparison between thecorrespondence table shown in FIG. 15 and the correspondence table shownin FIG. 3.

Exemplary Embodiment 2

FIG. 5 is a block diagram showing a structure of an image quantizationparameter decoder corresponding to the image quantization parameterencoder in Exemplary Embodiment 1. The image quantization parameterdecoder shown in FIG. 5 includes a predictor 201, a buffer 202, ade-binarizer 2031, an adaptive binary arithmetic decoder 204, a binaryarithmetic decoder 205, a switch (SW) 211, and a switch (SW) 212.

The de-binarizer 2031 computes cMax based on minDQP and maxDQP, by thefollowing equation.

cMax=max(|minDQP|,|maxDQP|)−1   (5).

The adaptive binary arithmetic decoder 204 binary arithmetic decodesbin(1) from the encoded data supplied via the switch 212, and suppliesthe decoded data to the de-binarizer 2031 via the switch 211. Theadaptive binary arithmetic decoder 204 also updates the contextassociated with the context index corresponding to the first binaccording to the value of the binary arithmetic decoded bin, forsubsequent binary arithmetic decoding.

In the case where bin(1) is 1, the adaptive binary arithmetic decoder204 binary arithmetic decodes bin(n) (n=2, 3, . . . , k, where k≦1 cMax)from the encoded data supplied via the switch 212, until a bin whosevalue is 0 is decoded, until cMax bins are decoded, or until a bin whosevalue is 0 is decoded and also cMax bins are decoded. The adaptivebinary arithmetic decoder 204 supplies the decoded data to thede-binarizer 2031 via the switch 211. The adaptive binary arithmeticdecoder 204 updates the context associated with the context indexcorresponding to the nth bin according to the value of the binaryarithmetic decoded bin, for subsequent binary arithmetic decoding.

Furthermore, in the case where bin(1) is 1, the binary arithmeticdecoder 205 binary arithmetic decodes the Signbin from the encoded datasupplied via the switch 212, and supplies the decoded data to thede-binarizer 2031 via the switch 211.

The de-binarizer 2031 outputs the DQP whose value is 0, in the casewhere the bin string is 0 (n=1). In the case where n=1+cMax, thede-binarizer 2031 outputs the DQP whose value is obtained by thefollowing equation.

DQP=(1−2*Signbin)*(1+cMax)   (6).

“* ” in equation (6) denotes multiplication. Otherwise, the de-binarizer2031 outputs the DQP whose value is obtained by the following equation.

DQP=(1−2*Signbin)*(n−1)   (7).

As is clear from equation (6), the de-binarizer 2031 can estimate anyredundant bin reduced in the video encoding process, using the DQP range(maximum value of the absolute values of the minimum DQP and the maximumDQP). That is, the de-binarizer 2031 can de-binarize the bins of the binstring made non-redundant, using the DQP range (maximum value of theabsolute values of the minimum DQP and the maximum DQP).

The PQP supplied from the predictor 201 is added to the DQP suppliedfrom the de-binarizer 2031, to obtain the RQP.

The RQP is stored in the buffer 202 for subsequent quantizationparameter decoding.

This completes the description of the structure of the imagequantization parameter decoder in this exemplary embodiment.

The following describes operations of the de-binarizer 2031, theadaptive binary arithmetic decoder 204, and the binary arithmeticdecoder 205 which are features of the image quantization parameterdecoder in this exemplary embodiment, using a flowchart in FIG. 6.

The process starts, with the adaptive binary arithmetic decoder 204setting an initial value parameter n to 2.

In step S301, the adaptive binary arithmetic decoder 204 adaptive binaryarithmetic decodes bin(1). p In step S302, the binary arithmetic decoder205 determines whether or not the value of bin(1) is 1. In the casewhere the value of bin(1) is 1, the process proceeds to step S303.Otherwise, the process proceeds to step S307.

In step S303, the de-binarizer 2031 computes cMax based on minDQP andmaxDQP.

In step S304, the adaptive binary arithmetic decoder 204 adaptive binaryarithmetic decodes bin(n).

In step S305, the adaptive binary arithmetic decoder 204 determineswhether or not all bins relating to |DQP| have been decoded. All binshave been decoded if a condition that the value of bin(n) is 0, acondition that the value of n is equal to cMax, or both of theseconditions are met. In the case where all bins relating to |DQP| havebeen decoded, the process proceeds to step S306. Otherwise, the adaptivebinary arithmetic decoder 204 increments n and the process proceeds tostep S304, to adaptive binary arithmetic decode the subsequent bin(n).

In step S306, the binary arithmetic decoder 205 binary arithmeticdecodes the Signbin.

In step S307, the de-binarizer 2031 de-binarizes the decoded bin stringto determine the DQP.

This completes the description of the operations of the de-binarizer2031, the adaptive binary arithmetic decoder 204, and the binaryarithmetic decoder 205 which are features of the image quantizationparameter decoder in this exemplary embodiment.

Exemplary Embodiment 3

In the image quantization parameter encoder in FIG. 1 and the imagequantization parameter decoder in FIG. 5 described above, minDQP andmaxDQP may be generated from the range of the quantization parameter(combination of a minimum QP and a maximum QP) and the predictedquantization parameter PQP.

FIGS. 7 and 8 are block diagrams showing structures of an imagequantization parameter encoder and an image quantization parameterdecoder as an improvement to generate minDQP and maxDQP based on thecombination of the minimum QP (minQP) and the maximum QP (maxQP) and thePQP.

The image quantization parameter encoder shown in FIG. 7 furtherincludes a range determiner 106, and the image quantization parameterdecoder shown in FIG. 8 further includes a range determiner 206, as canbe seen from the comparison with FIGS. 1 and 5. The range determiners106 and 206 each compute minDQP and maxDQP by the following equations.

minDQP=minQP−PQP   (8)

maxDQP=maxQP−PQP   (9).

The inclusion of the range determiners 106 and 206 enables moreeffective reduction of redundant bins when the QP to be encoded iscloser in value to minQP or maxQP.

FIG. 9 is an explanatory diagram showing a pseudo program for generatinga bin string corresponding to a DQP of a value synVal (note that the PQPis written as QP_(Y,PREV) in the pseudo program).

In an image quantization parameter encoder and an image quantizationparameter decoder where minDQP==26 and maxDQP=25, equations (8) and (9)may be replaced with the following equations (8)′ and (9)′.

minDQP=max(−26,minQP−PQP)   (8)′

maxDQP=min(25,maxQP−PQP)   (9)′.

The image quantization parameter encoder and the image quantizationparameter decoder according to the present invention described above mayoperate based on a correspondence table in which the value of thecontext index is fixed for bins from a predetermined column onward asshown in FIG. 10, instead of using the example shown in FIG. 3.

In the correspondence table shown in FIG. 10, the value of the contextindex is fixed at 3 for the bins in the third and subsequent columns. InFIG. 10, the first bin indicates only the information of whether or notthe DQP is significant, that is, information of which one of two statesholds true. The second bin indicates only the information of whether ornot the absolute value of the DQP is greater than 1, that is,information of which one of two states holds true. The third andsubsequent bins indicate only the information of whether or not the binstring terminates, that is, information of which one of two states holdstrue.

Thus, the image quantization parameter encoder according to the presentinvention may binary arithmetic encode the first bin indicating whetheror not the DQP is significant, the third bin indicating whether or notthe absolute value of the DQP is greater than 1, the bin indicatingwhether or not the bin string terminates, and the Signbin indicating thepositive or negative sign of the DQP.

As described above, according to the present invention, an imagequantization parameter for image encoding that uses con text-basedadaptive binary arithmetic coding can be suitably encoded by providing,in a binarization process in which the information indicating whether ornot the delta quantization parameter is significant is associated withthe first bin, the information indicating the absolute value of thesignificant delta quantization parameter is associated with the secondand subsequent bins, and the information indicating whether thesignificant delta quantization parameter is positive or negative isassociated with the sign bin, means for reducing other redundant binsusing the range of the delta quantization parameter defined in standardsor the like.

According to the present invention, the above-mentioned suitableencoding is achieved by three features: assigning an appropriate contextto each bin of the delta quantization parameter; reducing redundant binsof the delta quantization parameter; and reducing the number of binsincluded in the bin string of the delta quantization parameter.

Each of the exemplary embodiments described above may be realized notonly by hardware but also by a computer program.

An information processing system shown in FIG. 11 includes a processor1001, a program memory 1002, a storage medium 1003 for storing imagedata, and a storage medium 1004 for storing a bitstream. The storagemedium 1003 and the storage medium 1004 may be separate storage media,or storage areas included in the same storage medium. As a storagemedium, a magnetic storage medium such as a hard disk is available.

In the information processing system shown in FIG. 11, a program forrealizing the functions of the blocks (except the block of the buffer)shown in any of FIGS. 1, 5, 7, and 8 is stored in the program memory1002. The processor 1001 realizes the functions of the imagequantization parameter encoder or the image quantization parameterdecoder shown in any of FIGS. 1, 5, 7, and 8, by executing processesaccording to the program stored in the program memory 1002.

FIG. 12 is a block diagram showing characteristic components in an imagequantization parameter encoder according to the present invention. Asshown in FIG. 12, the image quantization parameter encoder according tothe present invention includes: a prediction unit 11 for generating apredicted quantization parameter from a past reconstructed quantizationparameter; a computing unit 12 for generating a delta quantizationparameter from a quantization parameter and the predicted quantizationparameter; a quantization parameter encoding unit 13 for binaryarithmetic encoding a first bin indicating whether or not the deltaquantization parameter is significant, other bins indicating an absolutevalue of the delta quantization parameter, and a bin indicating whetherthe delta quantization parameter is positive or negative, in the casewhere the delta quantization parameter is significant; and a redundancysuppression unit 14 for reducing one or more of the other bins using arange of the delta quantization parameter.

FIG. 13 is a block diagram showing characteristic components in an imagequantization parameter decoder according to the present invention. Asshown in FIG. 13, the image quantization parameter decoder according tothe present invention includes: a prediction unit 21 for generating apredicted quantization parameter from a past reconstructed quantizationparameter; a quantization parameter decoding unit 22 for binaryarithmetic decoding a first bin indicating whether or not a deltaquantization parameter is significant, other bins indicating an absolutevalue of the delta quantization parameter, and a bin indicating whetherthe delta quantization parameter is positive or negative; and anestimation unit 23 for estimating one or more of the other bins reducedin a video encoding process, using a range of the delta quantizationparameter.

Though the present invention has been described with reference to theabove exemplary embodiments and examples, the present invention is notlimited to the above exemplary embodiments and examples. Various changesunderstandable by those skilled in the art can be made to the structuresand details of the present invention within the scope of the presentinvention.

This application claims priority based on Japanese Patent ApplicationNo. 2011-153427 filed on Jul. 12, 2011, the disclosure of which isincorporated herein in its entirety.

Reference Signs List

-   11 prediction unit-   12 computing unit-   13 quantization parameter encoding unit-   14 redundancy suppression unit-   21 prediction unit-   22 quantization parameter decoding unit-   23 estimation unit-   101 predictor-   102 buffer-   1031, 1032 binarizer-   104 adaptive binary arithmetic encoder-   105 binary arithmetic encoder-   106 range determiner-   111 switch-   112 switch-   201 predictor-   202 buffer-   2031, 2032 de-binarizer-   204 adaptive binary arithmetic decoder-   205 binary arithmetic decoder-   206 range determiner-   211 switch-   212 switch

1-10. (canceled)
 11. An image quantization parameter decoding method for decoding a quantization parameter for a video decoding process that is based on context-based adaptive binary arithmetic coding, the image quantization parameter decoding method comprising: binary-arithmetic-decoding a first bin indicating whether or not a delta quantization parameter is significant, other bins, which are subsequent to the first bins indicating an absolute value of the delta quantization parameter, and a sign bin, which is subsequent to the other bins, indicating whether the delta quantization parameter is positive or negative; generating a delta quantization parameter by de-binarizing the first bin, the other bins and the sign bin; and generating a re-constructed quantization parameter by adding a predicted quantization parameter to the delta quantization parameter, wherein the binary-arithmetic-decoding is performed using contexts for the first bin and the other bins, and using no context for the sign bin.
 12. An image quantization parameter decoder for decoding a quantization parameter for a video decoding process that is based on context-based adaptive binary arithmetic coding, the image quantization parameter decoder comprising: a memory storing instructions; and a processor configured to execute the instructions to: decode by binary-arithmetic-decoding, a first bin indicating whether or not a delta quantization parameter is significant, other bins, which are subsequent to the first bin, indicating an absolute value of the delta quantization parameter, and a sign bin, which is subsequent to the other bins, indicating whether the delta quantization parameter is positive or negative; de-binarize the first bin, the other bins and the sign bin to generate a delta quantization parameter; and add a predicted quantization parameter to the delta quantization parameter to generate a re-constructed quantization parameter, wherein the binary-arithmetic-decoding is performed using contexts for the first bin and the other bins, and using no context for the sign bin. 